Bayesian Analysis for the Generalized Lognormal Distribution Applied to Failure Time Analysis

There are several versions of the lognormal distribution in the statistical literature, one is based in the exponential transformation of generalized normal distribution (GN). This paper presents the Bayesian analysis for the generalized lognormal distribution (logGN) considering independent non-informative Jeffreys distributions for the parameters as well as the procedure for implementing the Gibbs sampler to obtain the posterior distributions of parameters. The results are used to analyze failure time models with right-censored and uncensored data. The proposed method is illustrated using actual failure time data of computers.

Improved likelihood inference for the shape parameter in Weibull regression

We obtain adjustments to the profile likelihood function in Weibull regression models with and without censoring. Specifically, we consider two different modified profile likelihoods: (i) the one proposed by Cox and Reid [Cox, D.R. and Reid, N., 1987, Parameter orthogonality and approximate conditional inference. Journal of the Royal Statistical Society B, 49, 1-39.], and (ii) an approximation to the one proposed by Barndorff-Nielsen [Barndorff-Nielsen, O.E., 1983, On a formula for the distribution of the maximum likelihood estimator. Biometrika, 70, 343-365.], the approximation having been obtained using the results by Fraser and Reid [Fraser, D.A.S. and Reid, N., 1995, Ancillaries and third-order significance. Utilitas Mathematica, 47, 33-53.] and by Fraser et al. [Fraser, D.A.S., Reid, N. and Wu, J., 1999, A simple formula for tail probabilities for frequentist and Bayesian inference. Biometrika, 86, 655-661.]. We focus on point estimation and likelihood ratio tests on the shape parameter in the class of Weibull regression models. We derive some distributional properties of the different maximum likelihood estimators and likelihood ratio tests. The numerical evidence presented in the paper favors the approximation to Barndorff-Nielsen`s adjustment.

Different Approaches for Modeling Grouped Survival Data: A Mango Tree Study

Interval-censored survival data, in which the event of interest is not observed exactly but is only known to occur within some time interval, occur very frequently. In some situations, event times might be censored into different, possibly overlapping intervals of variable widths; however, in other situations, information is available for all units at the same observed visit time. In the latter cases, interval-censored data are termed grouped survival data. Here we present alternative approaches for analyzing interval-censored data. We illustrate these techniques using a survival data set involving mango tree lifetimes. This study is an example of grouped survival data.

A bivariate regression model for matched paired survival data: local influence and residual analysis

The use of bivariate distributions plays a fundamental role in survival and reliability studies. In this paper, we consider a location scale model for bivariate survival times based on the proposal of a copula to model the dependence of bivariate survival data. For the proposed model, we consider inferential procedures based on maximum likelihood. Gains in efficiency from bivariate models are also examined in the censored data setting. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and compared to the performance of the bivariate regression model for matched paired survival data. Sensitivity analysis methods such as local and total influence are presented and derived under three perturbation schemes. The martingale marginal and the deviance marginal residual measures are used to check the adequacy of the model. Furthermore, we propose a new measure which we call modified deviance component residual. The methodology in the paper is illustrated on a lifetime data set for kidney patients.

The beta-Birnbaum-Saunders distribution An improved distribution for fatigue life modeling

Birnbaum and Saunders (1969a) introduced a probability distribution which is commonly used in reliability studies For the first time based on this distribution the so-called beta-Birnbaum-Saunders distribution is proposed for fatigue life modeling Various properties of the new model including expansions for the moments moment generating function mean deviations density function of the order statistics and their moments are derived We discuss maximum likelihood estimation of the model s parameters The superiority of the new model is illustrated by means of three failure real data sets (C) 2010 Elsevier B V All rights reserved

Hydrolysis of acetic anhydride: Non-adiabatic calorimetric determination of kinetics and heat exchange

A simple calorimetric method to estimate both kinetics and heat transfer coefficients using temperature-versus-time data under non-adiabatic conditions is described for the reaction of hydrolysis of acetic anhydride. The methodology is applied to three simple laboratory-scale reactors in a very simple experimental setup that can be easily implemented. The quality of the experimental results was verified by comparing them with literature values and with predicted values obtained by energy balance. The comparison shows that the experimental kinetic parameters do not agree exactly with those reported in the literature, but provide a good agreement between predicted and experimental data of temperature and conversion. The differences observed between the activation energy obtained and the values reported in the literature can be ascribed to differences in anhydride-to-water ratios (anhydride concentrations). (C) 2010 Elsevier Ltd. All rights reserved.

A frailty modeling approach for parental effects in animal breeding

Survival models involving frailties are commonly applied in studies where correlated event time data arise due to natural or artificial clustering. In this paper we present an application of such models in the animal breeding field. Specifically, a mixed survival model with a multivariate correlated frailty term is proposed for the analysis of data from over 3611 Brazilian Nellore cattle. The primary aim is to evaluate parental genetic effects on the trait length in days that their progeny need to gain a commercially specified standard weight gain. This trait is not measured directly but can be estimated from growth data. Results point to the importance of genetic effects and suggest that these models constitute a valuable data analysis tool for beef cattle breeding.

Mechanical characterization of proanthocyanidindentin matrix interaction

Objectives To characterize the properties of dentin matrix treated with two proanthocyanidin rich cross-linking agents and their effect on dentin bonded interfaces. Methods Sound human molars were cut into 0.5mm thick dentin slabs, demineralized and either treated with one of two cross-linking agents (grape seedGSE and cocoa seedCOE extracts) or left untreated. The modulus of elasticity of demineralized dentin was assessed after 10 or 60min and the swelling ratio after 60min treatment. Bacterial collagenase was also used to assess resistance to enzymatic degradation of samples subjected to ultimate tensile strength. The effect of GSE or COE on the resindentin bond strength was evaluated after 10 or 60min of exposure time. Data were statistically analyzed at a 95% confidence interval. Results Both cross-linkers increased the elastic modulus of demineralized dentin as exposure time increased. Swelling ratio was lower for treated samples when compared to control groups. No statistically significant changes to the UTS indicate that collagenase had no effect on dentin matrix treated with either GSE or COE. Resindentin bonds significantly increased following treatment with GSE regardless of the application time or adhesive system used. Significance Increased mechanical properties and stability of dentin matrix can be achieved by the use of PA-rich collagen cross-linkers most likely due to the formation of a PAcollagen complex. The short term resindentin bonds can be improved after 10min dentin treatment.(C) 2010 Academy of Denta lMaterials. Published by Elsevier Ltd. All rights reserved.

Influences of surface and solvent on retention of HEMA/mixture components after evaporation

Objectives: This study examined the retention of solvents within experimental HEMA/solvent primers after two conditions for solvent evaporation: from a free surface or from dentine surface. Methods: Experimental primers were prepared by mixing 35% HEMA with 65% water, methanol, ethanol or acetone (v/v). Aliquots of each primer (50 mu l) were placed on glass wells or they were applied to the surface of acid-etched dentine cubes (2 mm x 2 mm x 2 mm) (n = 5). For both conditions (i.e. from free surface or dentine cubes), change in primers mass due to solvent evaporation was gravimetrically measured for 10 min at 51% RH and 21 degrees C. The rate of solvent evaporation was calculated as a function of loss of primers mass (%) over time. Data were analysed by two-way ANOVA and Student-Newman-Keuls (p < 0.05). Results: There were significant differences between solvent retention(%) and evaporation rate (%/min) depending on the solvent present in the primer and the condition for evaporation (from free surface or dentine cubes) (p < 0.05). For both conditions, the greatest amount of retained solvent was observed for HEMA/water primer. The rate of solvent evaporation for HEMA/acetone primer was almost 2- to 10-times higher than for HEMA/water primer depending whether evaporation occurred, respectively, from a free surface or dentine cubes. The rate of solvent evaporation varied with time, being in general highest at the earliest periods. Conclusions: The rate of solvent evaporation and its retention into HEMA/solvent primers was influenced by the type of the solvent and condition allowed for their evaporation. (C) 2009 Elsevier Ltd. All rights reserved.

Effect of Chelating Solutions on the Microhardness of Root Canal Lumen Dentin

Introduction: The greatest reduction in microhardness of the most superficial layer of dentin of the root canal lumen is desired. The use of chelating agents during biomechanical preparation of root canals removes smear layer, increasing the access of the irrigant into the dentin tubules to allow adequate disinfection, and also reduces dentin microhardness, facilitating the action of endodontic instruments. This study evaluated the effect of different chelating solutions on the microhardness of the most superficial dentin layer from the root canal lumen. Methods: Thirty-five recently extracted single-rooted maxillary central incisors were instrumented, and the roots were longitudinally sectioned in a mesiodistal direction to expose the entire canal extension. The specimens were distributed in seven groups according to the final irrigation: 15% EDTA, 10% citric acid, 5% malic acid, 5% acetic acid, apple vinegar, 10% sodium citrate, and control (no irrigation). A standardized volume of 50 mu L of each chelating solution was used for 5 minutes. Dentin microhardness was measured with a Knoop indenter under a 10-g load and a 15-second dwell time. Data were analyzed statistically by one-way analysis of variance and Tukey-Kramer multiple-comparison test at 5% significance level. Results: EDTA and citric acid had the greatest overall effect, causing a sharp decrease in dentin microhardness without a significant difference (p > .05) from each other. However, both chelators differed significantly from the other solutions (p < .001). Sodium citrate and deionized water were similar to each other (p > .05) and did not affect dentin microhardness. Apple vinegar, acetic acid, and malic acid were similar to each other (p > .05) and presented intermediate results. Conclusion: Except for sodium citrate, all tested chelating solutions reduced microhardness of the most superficial root canal dentin layer. EDTA and citric acid were the most efficient. (J Endod 2011;37:358-362)

Modified section method for laser-welding of ill-fitting cp Ti and Ni-Cr alloy one-piece cast implant-supported frameworks

P>This study aimed to verify the effect of modified section method and laser-welding on the accuracy of fit of ill-fitting commercially pure titanium (cp Ti) and Ni-Cr alloy one-piece cast frameworks. Two sets of similar implant-supported frameworks were constructed. Both groups of six 3-unit implant-supported fixed partial dentures were cast as one-piece [I: Ni-Cr (control) and II: cp Ti] and evaluated for passive fitting in an optical microscope with both screws tightened and with only one screw tightened. All frameworks were then sectioned in the diagonal axis at the pontic region (III: Ni-Cr and IV: cp Ti). Sectioned frameworks were positioned in the matrix (10-Ncm torque) and laser-welded. Passive fitting was evaluated for the second time. Data were submitted to anova and Tukey-Kramer honestly significant difference tests (P < 0 center dot 05). With both screws tightened, one-piece cp Ti group II showed significantly higher misfit values (27 center dot 57 +/- 5 center dot 06 mu m) than other groups (I: 11 center dot 19 +/- 2 center dot 54 mu m, III: 12 center dot 88 +/- 2 center dot 93 mu m, IV: 13 center dot 77 +/- 1 center dot 51 mu m) (P < 0 center dot 05). In the single-screw-tightened test, with readings on the opposite side to the tightened side, Ni-Cr cast as one-piece (I: 58 center dot 66 +/- 14 center dot 30 mu m) was significantly different from cp Ti group after diagonal section (IV: 27 center dot 51 +/- 8 center dot 28 mu m) (P < 0 center dot 05). On the tightened side, no significant differences were found between groups (P > 0 center dot 05). Results showed that diagonally sectioning ill-fitting cp Ti frameworks lowers misfit levels of prosthetic implant-supported frameworks and also improves passivity levels of the same frameworks when compared to one-piece cast structures.

The Kumaraswamy Weibull distribution with application to failure data

For the first time, we introduce and study some mathematical properties of the Kumaraswamy Weibull distribution that is a quite flexible model in analyzing positive data. It contains as special sub-models the exponentiated Weibull, exponentiated Rayleigh, exponentiated exponential, Weibull and also the new Kumaraswamy exponential distribution. We provide explicit expressions for the moments and moment generating function. We examine the asymptotic distributions of the extreme values. Explicit expressions are derived for the mean deviations, Bonferroni and Lorenz curves, reliability and Renyi entropy. The moments of the order statistics are calculated. We also discuss the estimation of the parameters by maximum likelihood. We obtain the expected information matrix. We provide applications involving two real data sets on failure times. Finally, some multivariate generalizations of the Kumaraswamy Weibull distribution are discussed. (C) 2010 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

Standard Values for Real-Time Transthoracic Three-Dimensional Echocardiographic Dyssynchrony Indexes in a Normal Population

Background: There is a paucity of information describing the real-time 3-dimensional echocardiography (RT3DE) and dyssynchrony indexes (DIs) of a normal population. We evaluate the RT3DE DIs in a population with normal electrocardiograms and 2- and 3-dimensional echocardiographic analyses. This information is relevant for cardiac resynchronization therapy. Methods: We evaluated 131 healthy volunteers (73 were male, aged 46 +/- 14 years) who were referred for routine echocardiography; who presented normal cardiac structure on electrocardiography, 2-dimensional echocardiography, and RT3DE; and who had no history of cardiac diseases. We analyzed 3-dimensional left ventricular ejection fraction, left ventricle end-diastolic volume, left ventricle end-systolic volume, and left ventricular systolic DI% (6-, 12-, and 16-segment models). RT3DE data were analyzed by quantifying the statistical distribution (mean, median, standard deviation [SD], relative SD, coefficient of skewness, coefficient of kurtosis, Kolmogorov-Smirnov test, D`Agostino-Pearson test, percentiles, and 95% confidence interval). Results: Left ventricular ejection fraction ranged from 50% to 80% (66.1% +/- 7.1%); left ventricle end-diastolic volume ranged from 39.8 to 145 mL (79.1 +/- 24.9 mL); left ventricle end-systolic volume ranged from 12.9 to 66 mL (27 +/- 12.1 mL); 6-segment DI% ranged from 0.20% to 3.80% (1.21% +/- 0.66%), median: 1.06, relative SD: 0.5482, coefficient of skewness: 1.2620 (P < .0001), coefficient of Kurtosis: 1.9956 (P = .0039); percentile 2.5%: 0.2900, percentile 97.5%: 2.8300; 12-segment DI% ranged from 0.22% to 4.01% (1.29% +/- 0.71%), median: 1.14, relative SD: 0.95, coefficient of skewness: 1.1089 (P < .0001), coefficient of Kurtosis: 1.6372 (P = .0100), percentile 2.5%: 0.2850, percentile 97.5%: 3.0700; and 16-segment DI% ranged from 0.29% to 4.88% (1.59 +/- 0.99), median: 1.39, relative SD: 0.56, coefficient of skewness: 1.0792 (P < .0001), coefficient of Kurtosis: 0.9248 (P = .07), percentile 2.5%: 0.3750, percentile 97.5%: 3.750. Conclusion: This study allows for the quantification of RT3DE DIs in normal subjects, providing a comparison for patients with heart failure who may be candidates for cardiac resynchronization therapy. (J Am Soc Echocardiogr 2008; 21: 1229-1235)

Usefulness of Proteinuria as a Prognostic Marker of Mortality and Cardiovascular Events Among Patients Undergoing Percutaneous Coronary Intervention (Data from the Evaluation of Oral Xemilofiban in Controlling Thrombotic Events [EXCITE] Trial)

Proteinuria was associated with cardiovascular events and mortality in community-based cohorts. The association of proteinuria with mortality and cardiovascular events in patients undergoing percutaneous coronary intervention (PCI) was unknown. The association of urinary dipstick proteinuria with mortality and cardiovascular events (composite of death, myocardial infarction, or nonhemorrhagic stroke) in 5,835 subjects of the EXCITE trial was evaluated. Dipstick urinalysis was performed before PCI, and proteinuria was defined as trace or greater. Subjects were followed up for 210 days/7 months after enrollment for the occurrence of events. Multivariate Cox regression analysis evaluated the independent association of proteinuria with each outcome. Mean age was 59 years, 21% were women, 18% had diabetes mellitus, and mean estimated glomerular filtration rate was 90 ml/min/1.73 m(2). Proteinuria was present in 750 patients (13%). During follow-up, 22 subjects (2.9%) with proteinuria and 54 subjects (1.1%) without proteinuria died (adjusted hazard ratio 2.83, 95% confidence interval [CI] 1.65 to 4.84, p <0.001). The severity of proteinuria attenuated the strength of the association with mortality after PCI (low-grade proteinuria, hazard ratio 2.67, 95% CI 1.50 to 4.75; high-grade proteinuria, hazard ratio 3.76, 95% CI 1.24 to 11.37). No significant association was present for cardiovascular events during the relatively short follow-up, but high-grade proteinuria tended toward increased risk of cardiovascular events (hazard ratio 1.45, 95% CI 0.81 to 2.61). In conclusion, proteinuria was strongly and independently associated with mortality in patients undergoing PCI. These data suggest that such a relatively simple and clinically easy to use tool as urinary dipstick may be useful to identify and treat patients at high risk of mortality at the time of PCI. (C) 2008 Elsevier Inc. All rights reserved. (Am J Cardiol 2008;102:1151-1155)

Wavelet correlation between subjects: A time-scale data driven analysis for brain mapping using fMRI

Functional magnetic resonance imaging (fMRI) based on BOLD signal has been used to indirectly measure the local neural activity induced by cognitive tasks or stimulation. Most fMRI data analysis is carried out using the general linear model (GLM), a statistical approach which predicts the changes in the observed BOLD response based on an expected hemodynamic response function (HRF). In cases when the task is cognitively complex or in cases of diseases, variations in shape and/or delay may reduce the reliability of results. A novel exploratory method using fMRI data, which attempts to discriminate between neurophysiological signals induced by the stimulation protocol from artifacts or other confounding factors, is introduced in this paper. This new method is based on the fusion between correlation analysis and the discrete wavelet transform, to identify similarities in the time course of the BOLD signal in a group of volunteers. We illustrate the usefulness of this approach by analyzing fMRI data from normal subjects presented with standardized human face pictures expressing different degrees of sadness. The results show that the proposed wavelet correlation analysis has greater statistical power than conventional GLM or time domain intersubject correlation analysis. (C) 2010 Elsevier B.V. All rights reserved.